prikaz prve stranice dokumenta Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking
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Scientific paper - Original scientific paper
Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking
Journal of biomolecular structure & dynamics, (2021); https://doi.org/10.1080/07391102.2021.1990131
Kandagalla, Shivananda; Novak, Jurica; Shekarappa, Sharath Belenahalli; Grishina, Maria A; Potemkin, Vladimir A; Kumbar, Bhimanagoud

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Kandagalla, S., Novak, J., Shekarappa, S. B., Grishina, M. A., Potemkin, V. A. & Kumbar, B. (2021). Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking. Journal of biomolecular structure & dynamics. doi: 10.1080/07391102.2021.1990131

Kandagalla, Shivananda, et al. "Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking." Journal of biomolecular structure & dynamics, 2021. https://doi.org/10.1080/07391102.2021.1990131

Kandagalla, Shivananda, Jurica Novak, Sharath Belenahalli Shekarappa, Maria A Grishina, Vladimir A Potemkin and Bhimanagoud Kumbar. "Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking." Journal of biomolecular structure & dynamics (2021). https://doi.org/10.1080/07391102.2021.1990131

Kandagalla, S., et al. (2021) 'Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking', Journal of biomolecular structure & dynamics. doi: 10.1080/07391102.2021.1990131

Kandagalla S, Novak J, Shekarappa SB, Grishina MA, Potemkin VA, Kumbar B. Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking. Journal of biomolecular structure & dynamics [Internet]. 2021 October 18 [cited 2025 January 08]. doi: 10.1080/07391102.2021.1990131

S. Kandagalla, J. Novak, S. B. Shekarappa, M. A. Grishina, V. A. Potemkin and B. Kumbar, "Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking", Journal of biomolecular structure & dynamics, October 2021. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:193:878070. [Accessed: 08 January 2025]

Metadata
Title (english)Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking
AuthorShivananda Kandagalla
AuthorJurica Novak
AuthorSharath Belenahalli Shekarappa
AuthorMaria A Grishina
AuthorVladimir A Potemkin
AuthorBhimanagoud Kumbar
Author's institutionUniversity of Rijeka
(Faculty of Biotechnology and Drug Development)
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Chemistry
Theoretical Chemistry
Abstract (english)
Kyasanur forest disease (KFD) is a tick-borne, neglected tropical disease, caused by KFD virus (KFDV) which belongs to Flavivirus (Flaviviridae family). This emerging viral disease is a major threat to humans. Currently, vaccination is the only controlling method against the KFDV, and its effectiveness is very low. An effective control strategy is required to combat this emerging tropical disease using the existing resources. In this regard, in silico drug repurposing method offers an effective strategy to find suitable antiviral drugs against KFDV proteins. Drug repurposing is an effective strategy to identify new use for approved or investigational drugs that are outside the scope of their initial usage and the repurposed drugs have lower risk and higher safety compared to de novo developed drugs, because their toxicity and safety issues are profoundly investigated during the preclinical trials in human/other models. In the present work, we evaluated the effectiveness of the FDA approved and natural compounds against KFDV proteins using in silico molecular docking and molecular simulations. At present, no experimentally solved 3D structures for the KFD viral proteins are available in Protein Data Bank and hence their homology model was developed and used for the analysis. The present analysis successfully developed the reliable homology model of NS3 of KFDV, in terms of geometry and energy contour. Further, in silico molecular docking and molecular dynamics simulations successfully presented four FDA approved drugs and one natural compound against the NS3 homology model of KFDV.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusAccepted
Peer reviewPeer review - international
Publication versionAccepted version
Journal titleJournal of biomolecular structure & dynamics
p-ISSN0739-1102
DOIhttps://doi.org/10.1080/07391102.2021.1990131
URN:NBNurn:nbn:hr:193:878070
Online first2021-10-18
Document URLhttp://bib.irb.hr/1175028
Type of resourceText
Access conditionsOpen access
Embargo expiration date: 2024-01-01
Terms of useLicence In copyright icon
Created on2022-09-02 13:07:18